Tumor-Aware, Adversarial Domain Adaptation from CT to MRI for Lung Cancer Segmentation.
Jue JiangYu-Chi HuNeelam TyagiPengpeng ZhangAndreas RimnerGig S. MagerasJoseph O. DeasyHarini VeeraraghavanPublished in: MICCAI (2) (2018)
Keyphrases
- domain adaptation
- lung cancer
- lymph nodes
- lung cancer patients
- pet ct
- cancer diagnosis
- medical images
- ground glass opacity
- brain tumors
- ct images
- computed tomography
- mri images
- medical imaging
- magnetic resonance imaging
- cancer cells
- lung nodules
- ct data
- computer tomography
- treatment planning
- positron emission tomography
- pet images
- cross domain
- pulmonary nodules
- image guided
- magnetic resonance images
- multiple sources
- labeled data
- deformable registration
- ct scans
- mr images
- semi supervised
- automatic segmentation
- brain mri
- test data
- transfer learning
- x ray
- magnetic resonance
- image reconstruction
- semi supervised learning
- anatomical structures
- machine learning
- sentiment classification
- accurate segmentation
- image registration
- partial volume
- brain tissue
- risk factors
- medical image analysis
- target domain
- three dimensional
- image segmentation